The present invention relates generally to a method and apparatus for scaling persistence data accumulated in a digital storage oscilloscope for display using interpolation.
Traditionally, digital storage oscilloscopes (DSOs) capture an electrical signal (waveform) and allow the user to view a trace of the captured signal in a time (x-axis) versus amplitude (y-axis) display. In addition to simply acquiring and displaying a single signal trace, DSOs can accumulate data from a periodic signal. This repeatedly (or continuously) captured and stored data is called persistence data. Persistence data is a powerful tool for analyzing signals, since it may reveal signal features and events not discernible in a single trace.
In conventional DSOs, the persistence data is constrained by the display system. This is because the persistence data is accumulated at the same scale as the display. For example, if the display is 600 pixels wide, the persistence data is accumulated in a buffer also having a width of 600 pixels. Once accumulated, the persistence data is transferred in its entirety into the display memory, without any scaling. The problem with this approach is that resizing the display forces a reset (and another accumulation) of the persistence data. Thus, any change in the scaling results in a reset of the persistence data, or in certain conditions scale changes are simply not accepted.
Because the operator may be looking for rare events, the more persistence data that is acquired the more useful it is in analyzing the signal. However, it may take a relatively long time to acquire enough data to be useful. Thus, any time the persistence data is reset, as when scaling or zooming the display, the user not only loses valuable information but must also wait for the persistence data to again accumulate.
Moreover, when an operator zooms-in on a portion of the persistence data, he generally desires to view additional detail in the current data, not to view a new set of persistence data. Anytime a new signal is acquired, there is a risk the new data will not have the same signal pathology (i.e. the same features).